Senior AI Backend Engineer

About This RoleAI processing…

Key Responsibilities

• 1
  Architect, design, develop and deploy our AI solutions and systems in production environments, ensuring reliability, high performance and scalability.
• 2
  Design and build the orchestrator service that coordinates AI components, data flows, and external services to deliver reliable, real-time insights to merchants
• 3
  Develop and maintain scalable ETL pipelines or MCPs that process and sync heterogeneous data (text, images, audio) from various sources into the AI system
• 4
  Build and optimise the LLM Gateway infrastructure, including authentication, rate limiting, load balancing, and vector database management for the RAG system
• 5
  Create robust, high-performance APIs capable of handling multimodal data structures and high-volume requests, ensuring low-latency and production-grade reliability
• 6
  Implement observability tooling — including telemetry, logging, and tracing — to support auditing, evaluation, and continuous improvement of AI interactions
• 7
  Mentor backend engineers on the team, contributing to engineering standards, code reviews, and a culture of technical excellence
• 8
  Collaborate and communicate closely with data scientists, product managers, developers and other business stakeholders to bring state-of-the-art AI solutions to Customer Support, enhancing customer experience and improving operational efficiency.

Requirements

• Bachelor's or master's degree in Computer Science, Engineering, or a related field.
• +6 years of experience developing software products (if they are ML or AI related is a plus)
• Advanced proficiency in Python, with hands-on experience building and scaling backend systems in production environments using tools like Kubernetes, Docker, Airflow, and Spark.
• Strong knowledge of cloud infrastructure (AWS, S3) and CI/CD practices, with a track record of shipping reliable, maintainable systems.
• Experience designing APIs and working with distributed data systems and message brokers such as Kafka or RabbitMQ.
• Comfort working at the intersection of backend engineering and AI — including familiarity with LLMs, GenAI tooling, and machine learning concepts.
• Experience with status monitoring using cloud-native tools or 3rd party (e.g. Prometheus, Cloudwatch, ...) and LLM traceability
• Excellent communication and collaboration skills to work effectively in cross-functional teams.
• Ability to adapt to a fast-paced, dynamic work environment and quickly learn new technologies and techniques.
• Strong team player (m/f/d) with the ability to work with diverse groups of people in a productive and agile manner

Perks & Benefits